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Current opinion in structural biology最新文献

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Innovative strategies for modeling peptide–protein interactions and rational peptide drug design 多肽-蛋白相互作用建模和合理多肽药物设计的创新策略
IF 6.1 2区 生物学
Current opinion in structural biology Pub Date : 2025-06-25 DOI: 10.1016/j.sbi.2025.103083
Lara Scharbert , Birgit Strodel
{"title":"Innovative strategies for modeling peptide–protein interactions and rational peptide drug design","authors":"Lara Scharbert ,&nbsp;Birgit Strodel","doi":"10.1016/j.sbi.2025.103083","DOIUrl":"10.1016/j.sbi.2025.103083","url":null,"abstract":"<div><div>This review highlights cutting-edge techniques for modeling peptide–protein interactions and advancing computer-aided peptide–drug design. We examine significant progress in generating peptide poses through docking and artificial intelligence (AI), assessing peptide flexibility via enhanced molecular dynamics simulations, and analyzing binding interactions through free energy calculations. Additionally, we discuss how these insights can inform the rational design of therapeutic peptides by utilizing free energy metrics and strategic modifications to enhance their binding affinity and therapeutic potential. Looking forward, further integrating AI will be crucial for optimizing peptide design and enhancing drug development efforts.</div></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"93 ","pages":"Article 103083"},"PeriodicalIF":6.1,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144472324","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Editorial overview: Protein folding and binding — With a little help from AI 编辑概述：蛋白质折叠和结合-与人工智能的一点帮助
IF 6.1 2区 生物学
Current opinion in structural biology Pub Date : 2025-06-23 DOI: 10.1016/j.sbi.2025.103068
Yana Bromberg, Benjamin Schuler
{"title":"Editorial overview: Protein folding and binding — With a little help from AI","authors":"Yana Bromberg,&nbsp;Benjamin Schuler","doi":"10.1016/j.sbi.2025.103068","DOIUrl":"10.1016/j.sbi.2025.103068","url":null,"abstract":"","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"94 ","pages":"Article 103068"},"PeriodicalIF":6.1,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144364565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Atomistic simulations of intact virus capsids: A computational challenge worth the scientific payoff 完整病毒衣壳的原子模拟：值得科学回报的计算挑战
IF 6.1 2区 生物学
Current opinion in structural biology Pub Date : 2025-06-21 DOI: 10.1016/j.sbi.2025.103082
Carolina Pérez-Segura, Juan R. Perilla, Jodi A. Hadden-Perilla
{"title":"Atomistic simulations of intact virus capsids: A computational challenge worth the scientific payoff","authors":"Carolina Pérez-Segura,&nbsp;Juan R. Perilla,&nbsp;Jodi A. Hadden-Perilla","doi":"10.1016/j.sbi.2025.103082","DOIUrl":"10.1016/j.sbi.2025.103082","url":null,"abstract":"<div><div>All-atom molecular dynamics (MD) simulations of intact virus capsids provide unparalleled insights into the functional motions of these complex macromolecular assemblies. Despite the computational challenges of simulating multimillion-atom systems, these simulations uniquely reveal the structural basis for emergent properties, including collective motions, allostery, selective permeability, and mechanical responses that are inaccessible through experimental methods. Capsid simulations also drive technological advancements in MD methodologies, analysis tools, and multiscale modeling, fostering broader innovations in structural biology and biophysics. Given next-generation computational resources, MD simulations will continue to illuminate virus biology, support antiviral drug discovery, and enhance preparedness for emerging viral diseases. Here, atomistic simulations of complete capsid assemblies are reviewed, and their role in elucidating fundamental principles of virus function and therapeutic targeting is discussed. Altogether, MD of intact capsids is a computational challenge worth the payoff.</div></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"93 ","pages":"Article 103082"},"PeriodicalIF":6.1,"publicationDate":"2025-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144330663","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Prediction of nucleic acid binding residues in protein sequences: Recent advances and future prospects 蛋白质序列中核酸结合残基的预测：最新进展和未来展望
IF 6.1 2区 生物学
Current opinion in structural biology Pub Date : 2025-06-21 DOI: 10.1016/j.sbi.2025.103085
Sushmita Basu , Yuedong Yang , Lukasz Kurgan
{"title":"Prediction of nucleic acid binding residues in protein sequences: Recent advances and future prospects","authors":"Sushmita Basu ,&nbsp;Yuedong Yang ,&nbsp;Lukasz Kurgan","doi":"10.1016/j.sbi.2025.103085","DOIUrl":"10.1016/j.sbi.2025.103085","url":null,"abstract":"<div><div>Computational prediction of DNA-binding residues (DBRs) and the RNA-binding residues (RBRs) in protein sequences is an active area of research, with about 90 predictors and 20 that were published over the last two years. The new predictors rely on sophisticated deep neural networks and protein language models, produce accurate predictions, and are conveniently available as code and/or web servers. However, we identified shortage of tools that predict these interactions in intrinsically disordered regions and tools capable of predicting residues that interact with specific RNA and DNA types. Moreover, cross-predictions between RBRs and DBRs should be quantified and minimized to ensure that future tools accurately differentiate between these two distinct types of nucleic acids.</div></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"94 ","pages":"Article 103085"},"PeriodicalIF":6.1,"publicationDate":"2025-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144331061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Artificial intelligence in therapeutic antibody design: Advances and future prospects 人工智能在治疗性抗体设计中的应用：进展和未来展望
IF 6.1 2区 生物学
Current opinion in structural biology Pub Date : 2025-06-18 DOI: 10.1016/j.sbi.2025.103084
Sujin Park , Wooyeop Jeong , Yubeen Kim , Chang-Han Lee , Chaok Seok
{"title":"Artificial intelligence in therapeutic antibody design: Advances and future prospects","authors":"Sujin Park ,&nbsp;Wooyeop Jeong ,&nbsp;Yubeen Kim ,&nbsp;Chang-Han Lee ,&nbsp;Chaok Seok","doi":"10.1016/j.sbi.2025.103084","DOIUrl":"10.1016/j.sbi.2025.103084","url":null,"abstract":"<div><div>In the few years since AlphaFold 2 revolutionized protein structure prediction, AI technologies have demonstrated strong potential for practical application in therapeutic antibody development, a key area in the pharmaceutical industry. This mini-review provides a concise overview of AI-driven approaches designed to precisely optimize antibody properties critical for successful therapeutics. In particular, protein structure prediction-based antibody design AI is advancing rapidly, facilitating the effective targeting of protein hotspots, as demonstrated in a few reported cases. These advancements are expected to streamline experimental workflows, reduce reliance on trial-and-error screening, and enable the efficient discovery of novel molecules that would be challenging to identify through traditional methods. Additionally, this review explores emerging AI methodologies aimed at optimizing Fc function, immunogenicity, and developability, offering insights into future directions in the field.</div></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"94 ","pages":"Article 103084"},"PeriodicalIF":6.1,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144306871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Entropy, enthalpy, and evolution: Adaptive trade-offs in protein binding thermodynamics 熵、焓和进化：蛋白质结合热力学中的适应性权衡
IF 6.1 2区 生物学
Current opinion in structural biology Pub Date : 2025-06-17 DOI: 10.1016/j.sbi.2025.103080
Rosemary Georgelin , Colin J. Jackson
{"title":"Entropy, enthalpy, and evolution: Adaptive trade-offs in protein binding thermodynamics","authors":"Rosemary Georgelin ,&nbsp;Colin J. Jackson","doi":"10.1016/j.sbi.2025.103080","DOIUrl":"10.1016/j.sbi.2025.103080","url":null,"abstract":"<div><div>Proteins are central to biological complexity as their ligand binding processes, shaped by thermodynamics, have driven evolutionary adaptation throughout Earth’s history. Despite extensive research into protein–ligand interactions, the evolution of their binding thermodynamics, particularly regarding enthalpy–entropy trade-offs, remains underexplored. This review compares experimental and computational findings to illustrate how the balance of thermodynamics influences protein structure and function over time. We hypothesize that ancient proteins likely exhibit entropically favored, flexible binding modes, while modern proteins increasingly rely on enthalpically driven specificity. Evolutionary trajectories, including those from ancestral sequence reconstruction studies and modern viral evolution, reveal that thermodynamic trade-offs allow proteins to adapt to diverse functions. Our evolutionary perspective on the existing research demonstrates that binding thermodynamics not only govern ligand affinity and specificity but also fundamentally shape protein evolution and inform potential protein engineering strategies.</div></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"94 ","pages":"Article 103080"},"PeriodicalIF":6.1,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144298654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Elucidating double stranded DNA viral scaffolding protein structures through advances in cryogenic electron microscopy data processing 通过低温电子显微镜数据处理的进展来阐明双链DNA病毒支架蛋白结构
IF 6.1 2区 生物学
Current opinion in structural biology Pub Date : 2025-06-16 DOI: 10.1016/j.sbi.2025.103081
Makayla N. Leroux , Garrett S. Skidds , Carolyn M. Teschke
{"title":"Elucidating double stranded DNA viral scaffolding protein structures through advances in cryogenic electron microscopy data processing","authors":"Makayla N. Leroux ,&nbsp;Garrett S. Skidds ,&nbsp;Carolyn M. Teschke","doi":"10.1016/j.sbi.2025.103081","DOIUrl":"10.1016/j.sbi.2025.103081","url":null,"abstract":"<div><div>Icosahedral double stranded DNA (dsDNA) virus assembly first necessitates the formation of a precursor capsid (procapsid) into which the DNA is packaged. Direct interactions between the major capsid protein (MCP) and a scaffolding protein promote proper procapsid assembly. The scaffolding protein can be an independent protein or a scaffolding-like domain covalently attached to the MCP that is comparable in structure and function. A full understanding of scaffolding protein structures has been limited by their intrinsically disordered nature. Advances in cryogenic electron microscopy (cryoEM) data processing techniques have provided new methodologies to help solve the structures of scaffolding proteins within procapsids. These structural insights further our understanding of how scaffolding proteins interact with the other assembly proteins to correctly construct the procapsid.</div></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"94 ","pages":"Article 103081"},"PeriodicalIF":6.1,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144298655","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Large-scale protein clustering in the age of deep learning 深度学习时代的大规模蛋白质聚类
IF 6.1 2区 生物学
Current opinion in structural biology Pub Date : 2025-06-13 DOI: 10.1016/j.sbi.2025.103078
Joana Pereira , Lorenzo Pantolini , Janani Durairaj , Torsten Schwede
{"title":"Large-scale protein clustering in the age of deep learning","authors":"Joana Pereira ,&nbsp;Lorenzo Pantolini ,&nbsp;Janani Durairaj ,&nbsp;Torsten Schwede","doi":"10.1016/j.sbi.2025.103078","DOIUrl":"10.1016/j.sbi.2025.103078","url":null,"abstract":"<div><div>Proteins within a family sharing sequence and structure similarity due to a common evolutionary origin often also share functional similarities. Clustering of proteins therefore offers valuable insights, enabling the transfer of features and annotations from well-studied proteins to less-investigated ones. On a local scale, clustering helps identify patterns within specific protein families. On a larger scale, it provides insights into the entire protein universe, showcasing relationships that may not be immediately apparent. Traditionally, this was done at the sequence level or with the use of experimentally resolved protein structures, but the advent of deep learning in protein bioinformatics has brought new options to the table, increasing the breadth, depth, and diversity of similarity metrics and clustering approaches.</div></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"94 ","pages":"Article 103078"},"PeriodicalIF":6.1,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144281131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Databases and web-based tools for studying structures of protein-nucleic acid complexes 研究蛋白质-核酸复合物结构的数据库和基于网络的工具
IF 6.1 2区 生物学
Current opinion in structural biology Pub Date : 2025-06-11 DOI: 10.1016/j.sbi.2025.103079
Justas Dapkūnas, Česlovas Venclovas
{"title":"Databases and web-based tools for studying structures of protein-nucleic acid complexes","authors":"Justas Dapkūnas,&nbsp;Česlovas Venclovas","doi":"10.1016/j.sbi.2025.103079","DOIUrl":"10.1016/j.sbi.2025.103079","url":null,"abstract":"<div><div>Structural data on protein-DNA and protein-RNA interactions are indispensable in molecular biology research. In this article, we review available databases and other web-based resources devoted to 3D structures of protein-nucleic acid complexes. First, we describe the core databases that collect and disseminate experimental data. We then review derivative databases focused specifically on structural data on protein-nucleic acid interactions. Finally, we provide an overview of several useful web servers for structure prediction, analysis and comparison. Tools for investigating protein-nucleic acid complexes are relatively scarce. This is primarily because the methods that integrate structural information from both proteins and nucleic acids are in short supply. However, the emerging AI-driven techniques for structure prediction are expected to boost the development of such methods.</div></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"94 ","pages":"Article 103079"},"PeriodicalIF":6.1,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144262728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Artificial intelligence methods for protein folding and design 蛋白质折叠与设计的人工智能方法
IF 6.1 2区 生物学
Current opinion in structural biology Pub Date : 2025-06-11 DOI: 10.1016/j.sbi.2025.103066
Zhidian Zhang , Chenxi Ou , Yehlin Cho , Yo Akiyama , Sergey Ovchinnikov
{"title":"Artificial intelligence methods for protein folding and design","authors":"Zhidian Zhang ,&nbsp;Chenxi Ou ,&nbsp;Yehlin Cho ,&nbsp;Yo Akiyama ,&nbsp;Sergey Ovchinnikov","doi":"10.1016/j.sbi.2025.103066","DOIUrl":"10.1016/j.sbi.2025.103066","url":null,"abstract":"<div><div>Machine learning has revolutionized protein structure prediction and design. This review discusses current methods for protein folding and inverse folding challenges. Models like AlphaFold2 (AF2), RoseTTAFold, and ESMFold excel at leveraging evolutionary information to accurately predict protein structures while still struggling to capture the physics of protein folding. Their repurposing for protein design has led to innovations such as RFdiffusion, AF2-design, and relaxed sequence optimization. ProteinMPNN and ESM-IF design sequences based on structure, so they are frequently referred to as “inverse folding’ methods. By examining the potential and limitations of current protein design methods and metrics, we provide perspectives on developing models that fully characterize energy landscapes associated with amino acid sequences. Such advances would enable more accurate structure prediction and the design of proteins with specified conformational dynamics, potentially transforming our ability to engineer novel proteins for biotechnological applications.</div></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"93 ","pages":"Article 103066"},"PeriodicalIF":6.1,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144253797","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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